/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.spark.scheduler.cluster.mesos

import org.apache.spark.SparkContext

private[spark] object MemoryUtils {
  // These defaults copied from YARN
  val OVERHEAD_FRACTION = 1.07
  val OVERHEAD_MINIMUM = 384

  def calculateTotalMemory(sc: SparkContext) = {
    math.max(
      sc.conf.getOption("spark.mesos.executor.memoryOverhead")
        .getOrElse(OVERHEAD_MINIMUM.toString)
        .toInt + sc.executorMemory,
        OVERHEAD_FRACTION * sc.executorMemory
    )
  }
}
